ALTO WG G. Bernstein
Internet-Draft Grotto Networking
Intended status: Standards Track Y. Lee
Expires: January 2, 2015 Huawei
W. Roome
M. Scharf
Alcatel-Lucent
Y. Yang
Yale University
July 1, 2014
ALTO Topology Extensions
draft-yang-alto-topology-02.txt
Abstract
The Application-Layer Traffic Optimization (ALTO) Service has defined
Network and Cost maps to provide basic network information. In this
document, we discuss an initial design to provide graph
representations of network topology, motivated by a basic use case of
multi-flow scheduling. The design is based on the ALTO WG
discussions at IETF 89.
Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at http://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on January 2, 2015.
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Copyright Notice
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document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
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described in the Simplified BSD License.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Review: the Base Single-Node Representation . . . . . . . . . 3
3. The Multi-flow Scheduling Use Case . . . . . . . . . . . . . 4
4. Path-Vector as Cost Metric Representation . . . . . . . . . . 5
5. Topology using Opaque Network Elements . . . . . . . . . . . 8
6. Topology using a Graph Representation . . . . . . . . . . . . 9
7. Graph Transformations to Build Topology/Overlays . . . . . . 12
8. Operations on Exported Topology . . . . . . . . . . . . . . . 13
9. Security Considerations . . . . . . . . . . . . . . . . . . . 14
10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 14
11. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 14
12. References . . . . . . . . . . . . . . . . . . . . . . . . . 14
12.1. Normative References . . . . . . . . . . . . . . . . . . 14
12.2. Informative References . . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15
1. Introduction
Topology is a basic information component that a network can provide
to network management tools and applications. Example tools and
applications that can utilize network topology include traffic
engineering, network services (e.g., VPN) provisioning, PCE,
application overlays, among others [RFC5693,I-D.amante-i2rs-topology-
use-cases, I-D.lee-alto-app-net-info-exchange].
A basic challenge in exposing network topology is that there can be
multiple representations of the topology of the same network
infrastructure, and each representation may be better suited for its
own set of deployment scenarios. For example, the current ALTO base
protocol [I-D.ietf-alto-protocol] is designed for a setting of
exposing network topology using the extreme "my-Internet-view"
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representation, which abstracts a whole network as a single node that
has a set of access ports, with each port connects to a set of
endhosts. The base protocol refers to each access port as a PID.
This "single-node" abstraction achieves simplicity and provides
flexibility. A problem of this abstraction, however, is that the
base protocol as currently defined does not provide enough
information for use cases such as multiflow scheduling (see
Section 2).
An opposite of the single-node representation is the complete raw
topology, spanning across multiple layers, to include all details of
network states such as endhosts attachment, physical links, physical
switch equipment, and logical structures (e.g., LSPs) already built
on top of physical infrastructural devices. A problem of the raw
topology representation, however, is that its exposure may violate
privacy constraints. Also, a large raw topology may be overwhelming
and unnecessary for specific applications. As typical ALTO clients
are not NMS systems and hence there is no need to access the full
RIB.
This document specifies a new type of ALTO Information Resources,
which provide graph representations of a network. We call such
Information Resources ALTO Topology Maps, or Topology Maps for short.
Different from the base single-node abstraction, a Topology Map
includes multiple network nodes. Different from the raw topology
representation that uses real network nodes, Topology Maps use
abstract nodes, although they should be constructed from the real,
raw topology, in order to provide grounded information. The design
of this document is based on the ALTO WG discussions at IETF 89, with
summary slides at http://tools.ietf.org/agenda/89/slides/slides-89-
alto-2.pdf.
The organization of this document is organized as follows. We first
review the ALTO base protocol in Section 2. Then in Section 3, we
give the multi-flow scheduling use case as an example. In Section 4,
we specify path vector as a key component to handle multi-flow
scheduling. In Section 5, we give two graph representations complete
the design. Section 6 gives a framework of topology transformations
to help with the understanding of deriving multiple representations
of the topology of the same network infrastructure.
2. Review: the Base Single-Node Representation
We distinguish between endhosts and the network infrastructure of a
network. Endhosts are sources and destinations of data that the
network infrastructure carries. The network itself is neither the
source nor the destination of data.
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For the given network, it provides "access ports" or access points
where digital signal from endhosts enter and leave the network. One
should understand "access ports" in a generic sense. For example, an
access port can be a physical Ethernet port connecting to a specific
endhost, or it can be a port connecting to a CE which connects to a
large number of endhosts. Let AP be the set of access ports (AP)
that the network provides.
A high-level abstraction of a network topology is only the set AP,
and one can visualize the network as a single, abstract node with the
set AP of access ports attached. At each ap in AP, a set of endhosts
can be reached as destinations. Let dest(ap) denote the set of
endhosts reachable at ap.
There can be multiple ways to partition the set AP. Each partition
is called a Network Map. Given a complete partition of AP, the ALTO
base protocol introduces PID to represent each partition subset. The
ALTO base protocol then conveys the pair-wise connection properties
from one PID to another PID through the "single-node". This is the
Cost Map.
3. The Multi-flow Scheduling Use Case
There are use cases where simple Cost Metric cannot convey enough
information to the applications about pair-wise connection properties
from one PID to another PID. Consider an application overlay which
needs to schedule the traffic among a set of endhost source-
destination pairs, say eh1 -> eh2, and eh3 -> eh4. Simple Cost
Metric such as 'available bw' for eh1 -> eh2 and eh3 -> eh4 may not
reflect whether the two paths for eh1 -> eh2 and eh3 -> eh4 share a
bottleneck.
More concretely, assume that the network has 7 switches (sw1 to sw7)
forming a dumb-bell topology. Switches sw1/sw3 provide access on one
side, s2/s4 provide access on the other side, and sw5-sw7 form the
backbone. Endhosts eh1 to eh4 are connected to access switches sw1
to sw4 respectively. Assume that the bandwidth of each link is 100
Mbps. Assume that the network is abstracted with 4 PIDs, with each
representing the hosts at one access switch.
Now, consider a Cost Map providing end-to-end available bandwidth.
There can be two possible interpretations on the semantics of the
value of PIDi -> PIDj reported by the Cost Map: (1) it represents
reserved bandwidth from PIDi -> PIDj, or (2) it represents possible
bandwidth for PIDi -> PIDj, if no other applications use shared
resources. The common understanding is (2), just as when we look at
the number of available seats on a flight.
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Assume that the application receives from the Cost Map that both PID1
-> PID2 and PID3 -> PID4 have bandwidth 100 Mbps. It cannot
determine that if it schedules the two flows together, whether it
will obtain a total of 100 Mbps or 200 Mbps. This depends on whether
the flows share a bottleneck:
o If PID1 -> PID2 and PID3 -> PID4 use different paths, for example,
when the first uses sw1 -> sw5 -> sw7 -> sw2, and the second uses
sw3 -> sw5 -> sw6 -> sw7 -> sw4. Then the application will obtain
200 Mbps.
o If PID1 -> PID2 and PID3 -> PID4 share the bottleneck, for
example, when both use the direct link sw5 -> sw7, then the
application will obtain only 100 Mbps.
To distinguish the two possible cases, the network needs to provide
more details.
4. Path-Vector as Cost Metric Representation
A key component to address the problem in the preceding section is to
introduce path vectors as a Cost Metric, which is a set of path
vectors from a source PID to a destination PID, where each path
vector is a sequence (array) of network elements.
A schema for introducing path vectors in Cost Maps is the following
extension of Section 11.2.3.6 of [I-D.ietf-alto-protocol]:
object {
cost-map.DstCosts.JSONValue -> JSONString<0,*>;
meta.cost-mode = "path-vector";
} InfoResourcePVCostMap : InfoResourceCostMap;
Specifically, the preceding specifies that InfoResourcePVCostMap
extends InfoResourceCostMap. The body specifies that the first
extension is achieved by changing the type of JSONValue defined in
DstCosts of cost-map to be an array of JSONString; the second
extension is that the cost-mode of meta MUST be "path-vector".
An example Cost Map using path-vector is the following:
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GET /costmap/pv HTTP/1.1
Host: alto.example.com
Accept: application/alto-costmap+json,application/alto-error+json
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HTTP/1.1 200 OK
Content-Length: TDB
Content-Type: application/alto-costmap+json
{
"meta" : {
"dependent-vtags" : [
{ "resource-id": "my-default-network-map",
"tag": "3ee2cb7e8d63d9fab71b9b34cbf764436315542e"
},
{"resource-id": "my-topology-map", // See below
"tag": "4xee2cb7e8d63d9fab71b9b34cbf76443631554de"
}
],
"cost-type" : {"cost-mode" : "path-vector"
}
},
"cost-map" : {
"PID1": { "PID1":[],
"PID2":["ne56", "ne67"],
"PID3":[],
"PID4":["ne57"]
},
"PID2": { "PID1":["ne75"],
"PID2":[],
"PID3":["ne75"],
"PID4":[]
},
"PID3": { "PID1":[],
"PID2":["ne57"],
"PID3":[],
"PID4":["ne57"]
},
"PID4": { "PID1":["ne75"],
"PID2":[],
"PID3":["ne75"],
"PID4":[]}
}
}
The example illustrates that there are two key extensions to the ALTO
base protocol:
o It introduces a new "cost-mode" named path vector.
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o To indicate the resource that provides information on the elements
of path vectors (e.g., ["ne5", "ne67"] for the path vector from
PID1 to PID2, it introduces a new dependency. In the example, we
indicate that it is a resource named "my-topology-map".
5. Topology using Opaque Network Elements
A missing piece to complete the preceding design is how to represent
the information resource that provides information on the elements of
the path vectors. One simple approach is to introduce simple network
element property maps, which provide a mapping from a network element
to its properties such as bandwidth or shared risk link group (srlg).
A schema for the Network Element Property Map can be:
object-map {
JSONString -> NetworkElementProperties; // name to properties
} NetworkElementMapData;
object-map {
JSONString bw;
JSONString srlg<0,*>;
} NetworkElementProperties;
An example Network Element Property Map:
GET /nepmap HTTP/1.1
Host: alto.example.com
Accept: application/alto-nepmap+json,application/alto-error+json
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HTTP/1.1 200 OK
Content-Length: TBD
Content-Type: application/alto-nepmap+json
{
"meta" : {
"vtag": {
"resource-id": "my-topology-map",
"tag": "da65eca2eb7a10ce8b059740b0b2e3f8eb1d4785"
}
},
"nep-map" : {
"ne57" : {"bw" : 100, "srlg" : [1, 3]}, // link sw5->sw7
"ne75" : {"bw" : 100, "srlg" : [1, 3]}, // link sw7->sw5
"ne56" : {"bw" : 100, "srlg" : [1]}, // link sw5->sw6
"ne65" : {"bw" : 100, "srlg" : [1]}, // link sw6->sw5
"ne67" : {"bw" : 100, "srlg" : [3]}, // link sw6->sw7
"ne76" : {"bw" : 100, "srlg" : [3]}, // link sw7->sw6
}
}
An advantage of the representation is that it does not need to
distinguish network nodes vs network links.
6. Topology using a Graph Representation
A potential problem of the path vector representation is its lacking
of compactness. For example, suppose a network has N PIDs, then it
will need to represent N * (N-1) paths, if each source-destination
pair has one path computed using a shortest-path algorithm. On the
other hand, the underlying graph may have only O(F * N) elements,
where F is the average degree of the topology.
A graph representation of the example topology in the preceding
section has three components:
1. PIDs: {AP1, AP2, AP3}, which is already defined by base ALTO;
2. Nodes: {s1, s2, s3}; and
3. Links: {AP1 -- s1, AP2 -- s2, AP3 -- s3, s1 -- s2, s2 -- s3, s1
-- s3}.
A schema for the graph representation, based on the types already
defined in the base ALTO protocol, is the following:
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object {
TopologyMapData topology-map;
} InfoResourceTopologyMap : ResponseEntityBase;
object {
NodeMapData nodes;
LinkMapData links;
} TopologyMapData;
object-map {
JSONString -> NodeProperties; // node name to properties
} NodeMapData;
object {
JSONString type;
...
} NodeProperties;
object-map {
JSONString -> LinkProperties; // link name to properties
} LinkMapData;
object {
JSONString src;
JSONString dst;
JSONString type;
CostValue costs<0,*>;
} LinkProperties;
object {
CostMetric metric;
JSONValue value; // value type depends on metric type
} CostValue;
One complexity of the graph representation is multicast/broadcast
links. Assume that the link from sw5 -> sw7 is actually a wireless
link and the application may benefit in knowing that sw5 -> sw7 and
sw5 -> sw6 can be active simultaneously. In other words, sw5 ->
[sw6, sw7] is a broadcast link. Knowing such links can be beneficial
in settings such as wireless opportunistic routing.
An example using the schema:
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GET /topologymap HTTP/1.1
Host: alto.example.com
Accept: application/alto-topologymap+json,application/alto-error+json
HTTP/1.1 200 OK
Content-Length: TBD
Content-Type: application/alto-topologymap+json
{
"meta" : {
"vtag": {
"resource-id": "my-topology-map",
"tag": "da65eca2eb7a10ce8b059740b0b2e3f8eb1d4785"
}
},
"topology-map" : {
"nodes" : {
"sw1" : {"type" : "switch"},
"sw2" : {"type" : "switch"},
"sw3" : {"type" : "switch"},
"sw4" : {"type" : "switch"},
"sw5" : {"type" : "switch"},
"sw6" : {"type" : "switch"},
"sw7" : {"type" : "switch"}
},
"links" : {
"e1" : {"src" : PID1,
"dst" : "sw1",
"type": "bidirected";
"costs" : [
{"cost-metric" : "availbw", "value" : 100
},
{"cost-metric" : "srlg", value : [1, 3]}
]
},
"e2" : {"src" : PID2,
"dst" : "sw2",
...
},
"e3" : {"src" : PID3,
"dst" : "sw3",
...
},
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"e4" : {"src" : PID4,
"dst" : "sw4",
...
},
"e15" : {"src" : "sw1",
"dst" : "sw5",
...
},
"e35" : {"src" : "sw3",
"dst" : "sw5",
...
},
"e27" : {"src" : "sw2",
"dst" : "sw7",
...
},
"e47" : {"src" : "sw4",
"dst" : "sw7",
...
},
"e57" : {"src" : "sw5",
"dst" : "sw7",
...
},
"e56" : {"src" : "sw5",
"dst" : "sw6",
...
},
"e67" : {"src" : "sw6",
"dst" : "sw7",
...
}
}
}
}
Note that the preceding Graph Representation does not provide path
informatino. Hence, it should be used with the path-vector
representation, or in constraint-light settings where networks use
simple, public algorithms to compute routing and hence no need to
provide the path vectors explicitly.
7. Graph Transformations to Build Topology/Overlays
The preceding sections give a top-down derivation. In this section
we give a graph transformation framework to build the schema from a
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raw topology G(0). The network conducts transformations on G(0) to
obtain other topologies, with the following objectives:
1. Simplification: G(0) may have too many details that are
unnecessary for the receiving app (assume intradomain); and
2. Preservation of privacy: there are details that the receiving app
should not be allowed to see; and
3. Conveying of logical structure (e.g., MPLS paths already
computed); and
4. Conveying of capability constraints (the network can have
limitations, e.g., it uses only shortest path routing); and
5. Allow modular composition: path from one point to another point
is delegated to another app.
The transformation of G(0) is to achieve/encode the preceding. For
conceptual clarity, we assume that the network uses a given set of
operators. Hence, given a sequence of operations and starting from
G(0), the network builds G(1), to G(2), ...
Below is a list of basic operators that the network may use to
transform from G(n-1) to G(n):
o O1: Deletion of a switch/port/link from G(n-1);
o O2: Switch aggregation: a set Vs of switches are merged as one new
(logical) switch, links/ports connected to switches in Vs are now
connected to the new logical switch, and then all switches in Vs
are deleted;
o O3: Path representation: For a given extra path from A to R1 to R2
... to B in G(n-1), a new (logical) link A -> B is added; if the
constraint is that A -> must use the path, it will be put into the
Overlay;
o O4: Switch split: A switch s in G(n-1) becomes two (logical)
switches s1 and s2. The links connected to s1 is a subset of the
original links connected to s; so is s2.
8. Operations on Exported Topology
Going beyond the basic topology exposure from the network and
applications/tools, we anticipate that applications and tools can
derive results and feed to topology. In particular, we consider the
following operations:
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o Instantiation of app guidance in real network: The details of
instantiation will be outside the scope of this document. Example
protocols include PCEP Extensions for Stateful PCE [I-D.ietf-pce-
stateful-pce], RSVP LSP's and their associated characteristics,
(i.e.: head and tail-end LSR's, bandwidth, priority, preemption,
etc.). The reason that we choose the preceding operator set is
that they are "implementable".
o We also anticipate topology guided mapping of other data: to allow
applications to subscribe to statistics and link status from the
derived topology.
9. Security Considerations
This document has not conducted its security analysis.
10. IANA Considerations
This document does not specified its IANA considerations, yet.
11. Acknowledgments
The author thanks discussions with Erran Li, Tianyuan Liu, Andreas
Voellmy, Haibin Song, and Yan Luo.
12. References
12.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
12.2. Informative References
[I-D.amante-i2rs-topology-use-cases]
Amante, S., Medved, J., Previdi, S., and T. Nadeau,
"Topology API Use Cases", draft-amante-i2rs-topology-use-
cases-00 (work in progress), February 2013.
[I-D.ietf-alto-protocol]
Alimi, R., Penno, R., and Y. Yang, "ALTO Protocol", draft-
ietf-alto-protocol-17 (work in progress), July 2013.
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[I-D.lee-alto-app-net-info-exchange]
Lee, Y., Bernstein, G., Choi, T., and D. Dhody, "ALTO
Extensions to Support Application and Network Resource
Information Exchange for High Bandwidth Applications",
draft-lee-alto-app-net-info-exchange-02 (work in
progress), July 2013.
[RFC5693] Seedorf, J. and E. Burger, "Application-Layer Traffic
Optimization (ALTO) Problem Statement", RFC 5693, October
2009.
Authors' Addresses
Greg Bernstein
Grotto Networking
Fremont, CA
USA
Email: gregb@grotto-networking.com
Young Lee
Huawei
TX
USA
Email: leeyoung@huawei.com
Wendy Roome
Alcatel-Lucent Technologies/Bell Labs
600 Mountain Ave, Rm 3B-324
Murray Hill, NJ 07974
USA
Phone: +1-908-582-7974
Email: w.roome@alcatel-lucent.com
Michael Scharf
Alcatel-Lucent Technologies
Germany
Email: michael.scharf@alcatel-lucent.com
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Y. Richard Yang
Yale University
51 Prospect St
New Haven CT
USA
Email: yry@cs.yale.edu
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